Bibliographic record
Abstract
Twenty-five years ago Islamic banking was virtually unknown.Now 55 developing and emerging market countries have some involvement with Islamic banking and finance. 1 In addition, there are Islamic financial institutions operating in 13 other locations: Australia, Bahamas, Canada, Cayman Islands, Denmark, Guernsey, Jersey, Ireland, Luxembourg, Switzerland, United Kingdom, United States and the Virgin Islands.In Pakistan, Iran and Sudan, all banks need to operate under Islamic financing principles.Elsewhere, in the mixed systems, the Islamic banks are in a minority and operate alongside conventional banks.Despite this expansion, Islamic banking remains poorly understood in many parts of the Muslim world and still continues to be almost an enigma in much of the West.Our objective is to provide a succinct analysis of the nature of Islamic banking and finance, accessible to a wide range of readers.In fact, the basic idea of Islamic banking can be stated simply.The operations of Islamic financial institutions primarily are based on a profit-andloss-sharing (PLS) principle.An Islamic bank does not charge interest but rather participates in the yield resulting from the use of funds.The depositors also share in the profits of the bank according to a predetermined ratio.There is thus a partnership between the Islamic bank and its depositors, on one side, and between the bank and its investment clients, on the other side, as a manager of depositors' resources in productive uses.This is in contrast with a conventional bank which mainly borrows funds at interest on one side of the balance sheet and lends funds at interest on the other.The complexity of Islamic banking comes from the variety (and nomenclature) of the instruments employed, and in understanding the underpinnings of Islamic law.In conducting this examination of the subject, the volume seeks to bring a different perspective on a number of aspects.First, in the analytical part of this study, there is an outline of the prohibition of interest (riba) according to the doctrines of Islamic economics, along with an analysis of the implications which follow from this ban for the character of financial intermediation and governance structures in Islamic financing.This analysis is undertaken against the backdrop of modern theories of financial intermediation which are concerned with transactions costs, information problems and the design of Mervyn K.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.060 | 0.020 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".